Feature recognition is a discipline focusing on the design and implementation of algorithms for detecting manufacturing information such as holes, slots, etc. in a solid model. Automated feature recognition has been an active research area in solid modeling for many years, and is considered to be a
Form feature recognition using convex decomposition: results presented at the 1997 ASME CIE Feature Panel Session
โ Scribed by Eric Wang; Yong Se Kim
- Book ID
- 104110625
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 437 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0010-4485
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โฆ Synopsis
This paper is a summary of the results we presented at the Feature Panel Session of the 1997 ASME Computers in Engineering Conference. Five participating groups submitted a total of nine test parts for feature recognition. To these test parts, we have applied our feature recognition method using a convex decomposition method called Alternating Sum of Volumes with Partitioning (ASVP). By applying combination operations to the ASVP decomposition of a part boundary, we obtain a Form Feature Decomposition (FFD) consisting of volumetric form features. The FFD can be further converted into application-specific feature representations, including the Negative Feature Decomposition (NFD) for machining or cast-then-machined applications. We describe an additional application of the ASVP algorithm to identify and filter out cylindrical features from a part boundary.
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